5  Final Data Dictionary

data_dictionary <- read.csv(file = here("_data/final_codebook.csv"))

data_dictionary %>% 
kbl(align = "c", 
      col.names = c("Variable Name", "Class/Type", "Definition", 
                    "Number of Unique Values", "Example Format")
) %>%
kable_styling(bootstrap_options = c("bordered")
) %>%
row_spec(0, 
         bold = TRUE, 
         background = "#0f172a",
         extra_css = "font-size: 16px!important;color:#ffffff;")

Variable Name	Class/Type	Definition	Number of Unique Values	Example Format
end_date	Date	last date of Epi week	31	format: 2023-06-03
start_date	Date	first date of Epi week	31	format: 2023-05-28
county	character	county of residence of cases	58	Alameda
health_officer_region	character	California Health Officer Region	6	Bay Area
race_coded	character	race category codes	7	1:07
race_long	character	race category full text	7	Black, Non-Hispanic
race_short	character	race category abbreviated text	7	Black NH
sex	character	sex categorization	2	FEMALE, MALE
age_cat	factor	age category	4	0-17, 18-49, 50-64, 65+
mmwr_week	factor	epi week 40 in 2022 to epi week 23 in 2023	31	22:52
mmwr_year	factor	year	1	2023
cumulative_infected	integer	total number of diagnosed individuals	NA	0 - 137804
cumulative_severe	integer	total number infected requiring hospitalization	NA	0 - 4060
cumulative_unrecovered	integer	total number unrecovered after a week of diagnosis	NA	0 - 16920
new_infections	integer	newly diagnosed individuals	NA	0 - 12110
new_severe	integer	newly identified cases requiring hospitalization	NA	0 - 352
new_unrecovered	integer	newly reported as unrecovered	NA	0 - 1436
pop	integer	estimated population by age group for year 2023	NA	0 - 980387
total_cnty_pop	integer	total population estimate by county	NA	1165 - 9825708
total_race_pop	integer	total county population by race/ethnicity	NA	0 - 4089110
total_sex_pop	integer	total county pouplation by sex	NA	548 - 5049625
total_HOR_pop	integer	total population by Health Officer Region	NA	683715 - 12802429